Formulating practical solutions for the reduction of problematic noise is an active area of engineering research in both the fields of acoustics and control. To date, noise reduction has been mostly carried out using passive means. These passive methods almost always require the installation of heavy, bulky and costly materials such as foams, wools and fibrous bats. The additional weight bulk and physical change required is in many situations neither practicable nor cost effective. Also, one of the fundamental problems with insulators or absorbing materials is that they do not work well at reducing noise at the low frequencies. This is primarily because the acoustic wavelength at low frequencies becomes large compared to the thickness of typical absorbent materials. Furthermore, all existing noise reduction systems utilize the feedback technique in closed environments, which are not ideal for the cancellation of random noise.
For example, U.S. Pat. No. 7,853,024 issued to Slapak et al., discloses an active noise control for controlling a noise produced by a noise source. The prior art's complicated prediction is based on the received signal (noise samples) and does not involve a primary transducer that senses the signal ahead of time to account for the dynamic changes of the random noise.
Active noise reduction can overcome these problems and disadvantages. Active noise reduction is based on the principle of superposition of signals. According to the principle of superposition, if two signals exist, one an undesired disturbance, the other a controlled response, their combined effect can be made zero if they are equal in magnitude and opposite in phase. This signal cancellation phenomenon is commonly termed destructive interference, and is a basis for the operation of active noise reduction systems.
The advantages of active noise reduction are numerous. However, the two most significant relate to the method's spectral effectiveness and method of installation.
Active noise reduction exploits the long wavelengths associated with low frequency sound. Active noise reduction systems are, therefore, more effective at attenuating low frequency acoustic disturbances. Such low frequency disturbances are the common undesired side effect of operating machinery and are difficult to reduce using passive techniques.
In terms of physical implementation, active noise reduction systems typically comprise small and light weight components. This means that active noise reduction systems can be used in many situations where passive methods are impractical due to their bulk, weight and cost effectiveness.
The existing active noise reduction systems still suffer from their own disadvantages, however. These include the risks associated with system stability, less than adequate noise suppression performance and insufficient operating bandwidth.
Active noise reduction systems based on a feedback control approach, for example, risk instability, particularly where the feedback compensator has no means of accounting for change in the dynamic characteristics of the plant. It is difficult to design a feedback compensation network that provides both highly effective and robust noise reduction, particularly over a wide frequency bandwidth. Also, as the feedback compensator's gain is increased to improve low frequency noise suppression, amplification at the higher frequencies typically impacts negatively on performance.
Active noise reduction systems based on the known adaptive feed-forward technique, for example, can experience problems with effective parameter convergence and therefore provide less than optimal performance. Adaptive techniques also require intensive processing particularly where the feed-forward path dynamics are complex and the time available to compute a control response is brief. In many cases this makes this method of control unfeasible due to cost or the inability to implement the system practically.